understanding customer needs

UNDERSTANDING CUSTOMER NEEDS

Barry L. BayusKenan-Flagler Business School

University of North CarolinaChapel Hill, NC 27599

(919)[email protected]

January 2005Revised November 2007

prepared for Shane, S. (ed.), Blackwell Handbook of Technology and Innovation Management, Cambridge, MA: Blackwell Publishers

The comments of the following people on an earlier draft are greatly appreciated: Sridhar Balasubramanian, Dick Blackburn, Paul Bloom, Ed Cornet, Ely Dahan, Abbie Griffin, Steve Hoeffler, Erin MacDonald, Jackki Mohr, Bill Moore, Vithala Rao, Allan Shocker, and Gal Zauberman.

mailto:[email protected]

Introduction

Touted as the “most significant category innovation since toilet paper first

appeared in roll form in 1890,” dispersible (flushable) moist toilet tissue on a roll was

introduced in the United States by Kimberly Clark in 2001. According to a corporate

press release, Cottonelle Fresh Rollwipes was a breakthrough product that “delivers the

cleaning and freshening of pre-moistened wipes with the convenience and disposability

of toilet paper.” Internal market research seemed to indicate that there was a clear

customer need for a new product to supplement dry toilet paper. Surveys and focus

groups revealed that over 60% of adult consumers had experimented with a moist

cleaning method (e.g., using baby wipes, wetting a washcloth, sprinkling water on dry

toilet paper) and one out of four used a moist cleaning method daily. Kimberly Clark

made the obvious connection that a majority of US consumers found dry toilet paper to

be limited for their real needs. Convinced that there was a huge market opportunity for a

more convenient product that addressed this consumer need for a cleaner and more

refreshing bathroom tissue, Kimberly Clark obtained more than 30 patents on a new

product and dispenser and invested over $100 million in R&D and manufacturing to

bring their Cottonelle Fresh Rollwipes to market. Backed by over $40 million in

marketing programs, sales were expected to reach $150 million in the first year and $500

million by six years. Perhaps more important, a significant increase in the $4.8 billion

US toilet paper market was anticipated since this innovation was a supplement, not

substitute, for existing products. Procter & Gamble also believed that there was a market

opportunity for moist bathroom wipes; they quickly followed suit by introducing a

similar product, Charmin Fresh Mates, later that year.

But, consumers were unimpressed with these new products. Sales were well

below forecasts: Procter & Gamble abandoned its product after only two years and

Kimberly Clark’s product is confined to a regional market where executives say that sales

are so small that they are financially insignificant. Despite their market research, did

Kimberley Clark (and Procter & Gamble) really understand their customers’ needs in this

situation? The Fresh Rollwipes product was designed to be conveniently dispensed via a

refillable plastic container that cliped to the standard toilet paper holder. Careful

attention was paid to developing a dispenser that blended in with the consumer’s

bathroom. Both companies, however, underestimated the role of consumer

embarrassment associated with toileting (e.g., Associated Press 2003). While many

consumers already used some sort of makeshift wet cleaning method in the bathroom,

they didn’t like others knowing about it. The extra dispenser attached to the holder is

right out in the open, possibly causing guests to wonder if there is something wrong with

household members since they were using these “alternative” wipes. Although

numerous mistakes were made in this case (e.g., Nelson 2002), it seems clear that

Kimberly Clark and Procter & Gamble did not completely understand their customers’

needs.

Unfortunately, this example is not unique. New product failure rates of up to 90

percent commonly cited in the popular and academic press suggest that successful

innovation is the exception rather than the rule (e.g., Power 1992; 1993; Stevens and

Burley 1997; Brand Strategy 2003). The road to riches is littered with many stories of

new product failure (e.g., Schnaars 1989; Gershman 1990; Kirchner 1995; McMath and

Forbes 1998; Franklin 2003). Not surprisingly, many pundits take these failures to mean

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that it is impossible to truly understand customer needs. Headlines like “Ignore Your

Customer” (Martin 1995), “Shoot First, Do Market Research Later” (Elliot 1998) and

statements like “The public does not know what is possible, we do” (Morita 1986) fuel

this viewpoint. At the same time however, a consistent finding from benchmarking

studies on the factors related to successful innovation is that understanding customer

needs is a fundamental, although challenging, activity (e.g., Montoya-Weiss and

Calantone 1994; Cooper 1999; Henard and Szymanski 2001). There are just as many, if

not more, examples in which firms used various traditional (e.g., customer surveys, focus

groups) and nontraditional (e.g., ethnography, contextual inquiry, empathic design)

research approaches to gain insight into their customers’ needs, and to develop highly

successful new products (e.g., Urban and Hauser 1993; Leonard-Barton 1995; Burchill, et

al. 1997; Otto and Wood 2001; Shillito 2001; Sanders 2002; Squires and Byrne (2002);

Crawford and Di Benedetto 2003; Ulrich and Eppinger 2004). Thus, there is persuasive

evidence that it is indeed possible to understand customer needs and that this insight can

be used in the innovation process. Rather than ignoring customers, it is more prudent to

only ignore customers’ specific ideas on how to fulfill their needs—it is the company’s

job to develop new products!

[insert Exhibit 1 about here]

Conceptually, understanding customer needs leads to products that are desirable,

feasible, and salable (to the mass market). Note that “product categories” are often

defined by firms and not by customers (e.g., the SLR camera category, the digital camera

category, the disposable camera category); thus product categories typically relate to

feasible combinations of attributes that are salable (and hopefully desirable). As

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suggested by Exhibit 1, ideas, concepts and new products can be classified based on their

location in the desirable-feasible-salable space. Thus, highly successful innovations are

desirable, feasible and salable. Casual observations indicate that many existing products

fall primarily in the feasible and salable region (e.g., Fresh Rollwipes), and that fresh

looks at already established categories can lead to more desirable new products (e.g.,

consider the efforts of Oxo in the kitchen tools market and its greatly acclaimed Good

Grips peeler, salad spinner and angled measuring cup). Gizmos and gadgets like the

Segway Human Transporter are mainly in the feasible and desirable overlap (e.g., Waters

and Field 2003), but are not really salable to the mass market. Many innovations that are

mainly technology-driven reside only in the feasible region for a number of years (e.g.,

directional sound systems for use in automobiles, advertising, and special office-based

applications; Schwartz 2004; brain-computer interfaces that allow the direct bi-

directional interfaces between the brain, nervous system and computer; Cyberkinetics

2004; Michelin’s Tweel, a single piece airless tire with “spokes” that never go flat;

Mayersohn 2005). Astute business analysts note that most firms are still product-driven

rather than customer-driven (i.e., firms first determine what is feasible for them to

develop; they then fashion marketing strategies to sell the products and services that can

deliver; only later finding out that their offerings may not really be desirable).

The primary purpose of this chapter is to review the theory and practice related to

understanding customer needs. By necessity, this review will be relatively brief as this

topic covers a wide spectrum of literature across the marketing, design, and engineering

disciplines. This review will provide insights into the challenges associated with

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identifying and interpreting customer needs, which will lead to a discussion of promising

directions for future research.

The Languages of Customer Needs

With respect to innovation and new product development, the language associated

with “customer needs” differs across the marketing, engineering, and industrial design

literatures. Different terminology is often used interchangeably: needs, wants, attributes,

features, requirements, specs, etc. For example, in their review of the product

development literature, Krishnan and Ulrich (2001) indicate that a useful representation

of a product is a vector of attributes, which they consider to also include customer needs,

customer requirements, product specifications, engineering characteristics, and technical

performance metrics. Even customers themselves often use these terms interchangeably

(e.g., Captain 2004). Customer needs are also context dependent (e.g., Green, et al.

2006), particularly with respect to usage (where and how the product is used), consumer

(who will use the product), and market (what competing products are available).

Any discussion of “needs” should probably start with Maslow’s (1954) widely

known hierarchy of needs theory1. According to Maslow, there are five levels of needs

ranging from basic needs that are present at birth to more complex psychological needs

that only become important once the lower level needs have been satisfied2. At the

lowest, basic level are biological and physiological needs (e.g., air, food, drink, shelter,

sleep, sex, etc.). The next level includes safety needs (e.g., security, order, law, etc.); this

is followed by belongingness and love needs (e.g., family, relationships, work group, to

1Another interesting technology “hierarchy” proposed by Farrell (1993) consists of shelter, health, communication, tools, packaging, raw materials, and transport. 2Maslow’s original theory has been modified by other researchers to include cognitive needs (e.g., knowing, understanding, etc.), aesthetic needs (e.g., beauty, symmetry, etc.), and transcendence needs (e.g., helping others to achieve self-actualization).

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be accepted, etc.), followed by esteem needs (e.g., achievement, independence,

recognition, prestige, etc.), and self-actualization needs (e.g., self-fulfillment, realizing

one’s potential, personal growth, etc.).

An important insight from Maslow’s theory is that there are different levels of

needs and needs form a hierarchy (that may allow for lexicographic decision processes;

e.g., see Olshavsky and Spreng 1996). For example, customers expect products to be

safe and useful. Products and services may be bought to perform certain tasks, as well as

to be accepted and recognized by others. Products may also satisfy aesthetic, as well as

self-actualization, needs. However, as noted by Sanders (1992) customers are not usually

very good at expressing their needs, especially higher level needs.

Customer needs are a description of the benefits desired by “customers”3 (e.g.,

Urban and Hauser 1993; Griffin and Hauser 1993)4. Needs are essentially what the

customer wants; needs are long-term in nature and can not always be recognized or

verbally described by a customer (Burchill and Brodie 1997; Burchill, et al. 1997; Shillito

2001; Mello 2003). Importantly, needs include utilitarian as well as hedonic benefits.

For example, customer needs associated with a digital camera might include “reliving

fond memories, feeling confident in taking pictures, taking great pictures.” Wants, on the

other hand, are things that a customer believes will fulfill a known need, are short-term

and temporary in nature, and can be easily influenced by psychosocial cues such as

3“Customer” is a general label that refers to the entire set of important stakeholders including the buyer, user, seller, and any others that are influenced by the innovation (e.g., Hauser 1993; Gershenson and Stauffer 1999; Karkkainen, et al. 2003; Molotch 2003). In other words, needs for the complete “customer chain” should be considered. For example, although buyers generally hate the “impervious” blister plastic wrap for small consumer electronic products, this clamshell packaging was actually designed to satisfy retailers’ need for theft reduction (Saranow 2004).

4Some consultants and strategy researchers prefer to think of needs as being the “jobs” customers are trying to get done when using a product or service (e.g., Christensen and Raynor 2003; Ulwick 2005). This is related to Griffin’s (1996) statement that needs are the problems that a product or service solves.

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advertising, personal recommendations, and norms (e.g., Hauser 1984; Shillito 2001).

For example, consumers may say they want an easy to use digital camera with at least 5.0

mega pixels, 32M internal memory, and video capability. (Problems are simply wants or

needs expressed in negative terms; Shillito 2001.)

Needs are concerned with “what” is desired by customers, whereas attributes,

features, requirements, and specifications deal with “how” a need is satisfied by a

specific product or service. In the economics literature, product characteristics are

defined to be the properties of a product that are relevant to consumer choice;

characteristics are quantitative in nature, can be measured objectively, and are universal

(e.g., Lancaster 1971; Rosen 1974; Ratchford 1975; Geisfeld, et al. 1977). Product

attributes are more abstract and generally fewer in number than product characteristics,

and are based on the perceptual dimensions that consumers use to make purchase

decisions (e.g., Kaul and Rao 1995)5. From the engineering and design literatures,

requirements are the engineering and technical solutions to meet a customer need and

specifications (specs) are the specific metrics associated with requirements (e.g., Shillito

2001; Otto and Wood 2001; Ulrich and Eppinger 2004)6. As implied by this discussion,

product characteristics, attributes, requirements and specs are closely related and

overlapping terms. For example, product characteristics for a digital camera might

include the number of mega pixels, the available megabits of image storage, battery life,

5Shocker and Srinivasan (1974) call product attributes that are meaningful to consumers and actionable by firms “actionable attributes.” Product features are generally concerned with specific attribute levels (Green 1974) or characteristics that can be specified in physical, chemical or financial terms (Johnson and Fornell 1987).

6Ulrich and Ellison (1999) further propose that requirements vary in the degree to which they are “holistic” (i.e., more holistic requirements are increasing in component complexity and the fraction of components on which performance depends). In related work, Martin (1999) develops a Generational Variety Index (a measure for the amount of redesign effort required for future product designs) and a Coupling Index (a measure of coupling among product components).

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and the number of automatic modes; product attributes could include the ease of use,

image quality, well-known brand, and battery life; customer requirements may include

usability, reliability, image quality and battery life; and product specs can include a 4x

optical zoom lens with 0.2x digital zoom, Li-Ion rechargeable battery, 5.0 mega pixels,

12 scene modes, etc.


To better grasp the challenges involved in understanding customer needs,

consider the example in Exhibit 2 (see also Woodruff and Gardial 1996; Ratneshwar, et

al. 1999). As discussed in Shillito (2001), there are at least three levels of customer

needs that are increasingly more abstract in scope: features, consequences, and desired

end-states. Features are often the words a consumer uses to describe a product or service

(e.g., a digital camera has an optical and digital zoom lens, auto flash and scene modes, a

long lasting battery, an easy interface to share photos, etc.). Features are concrete, short-

term in nature, and easy to influence. Incremental changes only result from focusing on

new products with improved features.

Consequences come from possession and/or use of the product or service. For

example, “a digital camera is simple and easy to use, gives me confidence, I feel like an

expert.” These expressions typically describe what the customer wants to have happen

and are frequently more emotional in nature. Designing new products to satisfy

consequences often leads to more creative and novel changes in existing products.

Desired end-states are the customer’s underlying purposes and goals (e.g., Pieters,

et al. 1995; Austin and Vancouver 1996; Huffman, et al. 2000). As such, they are long-

term and more abstract in nature (e.g., “a digital camera allows me to relive fond

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memories”). Developing innovations with these end-states in mind can result in creative

and radical changes since customer-oriented product-market structures may be very

different than traditional industry defined competitive boundaries (e.g., Day, et al. 1979;

Ratneshwar and Shocker 1991; Shocker, et al. 2004).

As implied by Exhibit 2, customers typically map many discrete and continuous

features onto fewer higher-level benefits (consequences and desired end-states) through a

process of cognitive abstraction (e.g., Johnson and Fornell 1987; Reynolds and Gutman

1988).


Exhibit 3 summarizes the discussion so far. The digital camera example

illustrates some of the ambiguity inherent in the language of new product development.

In some cases, needs, wants, attributes, features, requirements, and specs refer to the

same thing. In other instances, these terms capture very different information about what

the customer really desires. Highly successful innovations come from a deep

understanding of the utilitarian and hedonic benefits that customers desire, i.e., what is

widely referred to as customer needs. Importantly, customers cannot always recognize or

describe their needs in terms of consequences or end-states. Remember that customer

needs are not a particular “solution” (product or service), or a specific set of attributes,

specs, etc. As a result, a customer needs hierarchy almost always has to be interpreted

from the “raw” data of a customer research study. Several general approaches for

identifying customer needs will be discussed later in this chapter.

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Customer Needs in the Innovation Process

Exhibit 4 outlines the major steps involved in the “fuzzy front-end” of the

innovation process (e.g., Otto and Wood 2001; Ulrich and Eppinger 2004).

Understanding customer needs is a key input into what has become known as the voice of

the customer (VOC). Originating in the total quality management movement, the voice

of the customer and quality function deployment (QFD) enable marketing, design,

engineering, R&D, and manufacturing to effectively communicate across functional

boundaries (e.g., Hauser and Clausing 1988; Griffin and Hauser 1992; 1993; Shillito

2001; Dahan and Hauser 2002a; Akao and Mazur 2003). This cross-functional

communication is crucial to ensure that development efforts focus on innovations that are

feasible, salable and desirable (see Exhibit 1).

The voice of the customer includes identifying a set of detailed customer needs, as

well as summarizing these needs into a hierarchy where each need is prioritized7 with

respect to its customer importance (e.g., Griffin and Hauser 1993; Iansiti and Stein 1995).

Prioritizing customer needs is important since it allows the cross-functional development

team to make necessary tradeoff decisions when balancing the costs of meeting a

customer need with the desirability of that need relative to the entire set of customer

needs. The voice of the customer is then translated into requirements and product specs,

which in turn are translated into specific product attributes that can be bundled into

concepts and prototypes for further testing with customers (e.g., Dahan and Hauser

2002a; Pullman, et al. 2002; Ulrich and Eppinger 2004). Design researchers identify

three research platforms (Squires 2002): (1) discovery research (an open-ended

7There are several methods available for determining priorities, including subjective scoring by the development team as well as customer rating approaches and conjoint analysis (e.g., see Pullman, et al. 2002).

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exploratory effort to learn about customer culture so as to develop the foundation for

“really” new products and services), (2) definition research (which assumes there is

already a product concept, and thus define the products by identifying the customer

implications associated with specific designs, products, and marketing strategies), and (3)

evaluation research (which assumes there is already a working prototype, and thus helps

refine and validate prototypes, design usability, market segments, consumer preferences).


Practicing designers, as well as the sociology and anthropology literatures, tend to

emphasize methods for understanding the complete range of customer needs. For

example, many articles discuss ways to uncover embedded customer needs, including

empathic design methods (e.g., Leonard-Barton 1995; Leonard and Rayport 1997), user-

centered design (e.g., Norman and Draper 1986; Norman 1988; Abras, et al. 2004) and

contextual inquiry (e.g., Holtzblat and Beyer 1993) as well as ethnography and

nontraditional market research approaches (e.g., Beebe 1995; Patnaik and Becker 1999;

Wasson 2000; Kelley 2001; Squires and Byrne 2002; Kumar and Whitney 2003; Masten

and Plowman 2003). Used to develop the highly successful Mazda Miata Roadster8,

Kansei engineering has also been proposed as a way to expand customer needs

information to include customer feelings and other hedonic benefits (e.g., Nagamachi

1995; 2002). And, researchers have suggested ways to incorporate aesthetics, emotions

and experiential aspects into the identification of customer needs (e.g., Patton 1999;

8In the early 1990’s, Mazda wanted to develop a brand new sports car for the young adult market. As part of the Kansei process of videotaping and photographing young drivers maneuvering, steering, and controlling cars, the project team concluded that “unification of driver-machine” was the key desired end-state. As part of the design specifications, a particular sound of engine thrust was highly desired by the target customers. After extensive simulations and study of low frequency sounds with odd cycle combustion noise, a special exhaust pipe was developed that closely matched the desired sound. See Nagamachi (2002) and QFD Institute (2004).

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Schmitt 1999; Desmet, et al. 2001; Desmet 2003). Some research also addresses the

topic of determining priorities, including the use of direct rating scales (Wilkie and

Pessemier 1973; Griffin and Hauser 1993), the analytic hierarchy process (Saaty 1988),

conjoint analysis (e.g., Green and Srinivasan 1990; Green, et al. 2001), Borda counts

(Dym, et al. 2002) and fuzzy/entropy methods (Chan, et al. 1999).

The engineering, quality, and operations literatures consider a new product to be a

complex assembly of interacting components for which various parametric models are

built to optimize performance objectives (e.g., Otto and Wood 1998; McAdams, et al.

1998; Krishnan and Ulrich 2001; Aungst, et al. 2003). According to Michalek, et al.

(2005, p43), “engineers generally use intuition when dealing with customer needs,

emphasizing the creativeness and functionality of the product concept and working

toward technical objectives such are reliability, durability, environmental impact, energy

use, heat generation, manufacturability, and cost reduction, among others.” Given a set

of customer requirements and product specs, as well as related information on priorities,

optimal values for key design variables can be determined using various standard

techniques (Papalambros and Wilde 2000). Michalek, et al. (2005) describe how the

analytical target cascading method can be used to resolve technical tradeoffs by explicitly

recognizing designs that are costly and/or impossible to achieve.

By and large, the marketing literature does not directly deal with understanding

customer needs (e.g., Tauber 1974; Sanders 1992; Eliashberg, et al. 1995); instead, it

either implicitly or explicitly focuses on the concept generation and testing stage in the

innovation process (see Exhibit 4). To facilitate communication between marketing and

engineering, the marketing literature generally considers a new product or service to be a

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bundle of “actionable” attributes and characteristics (e.g., see the reviews in Kaul and

Rao 1995; Krishnan and Ulrich 2001). However, as noted by Shocker and Srinivasan

(1974; 1979) this approach is only “useful for locating ‘new’ product opportunities which

may not be substantially different from current alternatives” (Shocker and Srinivasan

1979, p164). Most of the extensive marketing research dealing with product positioning

and conjoint analysis assumes that determinant attributes have already been identified

(e.g., see the reviews in Green 1975; Shocker and Srinivasan 1979; Green and Srinivasan

1990; Urban and Hauser 1993; Kaul and Rao 1995; Srinivasan, et al. 1997; Green, et al.

2001), although novel applications are still possible (e.g., see the work of Moskowitz-

Jacobs in developing new foods and beverages). Moreover, marketing generally does not

completely appreciate the complex interactions and constraints among product specs in

developing a fully working product; marketing also usually underestimates the fact that

some designs are totally infeasible (e.g., Aungst, et al. 2003; Michalek, et al. 2005).

The discussion to this point highlights that different research streams separately

emphasize each of the critical steps in the innovation process in Exhibit 4. Moreover, the

engineering and marketing (and related economics) literatures typically deal with product

characteristics and attributes rather than a broader set of customer needs as defined in this

chapter (see Exhibits 2 and 3). Since it is very challenging to systematically develop new

products that are feasible, salable and desirable without completely understanding

customer needs, the relatively large number of failures reported in the press should not be

that surprising (see Exhibit 1).

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Identifying Customer Needs

One widely cited approach for determining the types of customer needs is the

Kano Model of Customer Satisfaction (Kano, et al. 1984)9. Kano developed his model by

adapting the ideas of Fredrick Herzberg on the asymmetry of the factors related to job

satisfaction and dissatisfaction (i.e., job satisfaction is related to “motivators” like

achievement, recognition, work itself, responsibility, whereas job dissatisfaction is

related to “hygiene” factors like company policy, relationship with supervisor, work

conditions, salary; Herzberg, et al. 1959; Herzberg 1968). In the 1970’s, Kano was

working with the Konica camera company to develop some highly differentiated new

products (e.g., Scholtes 1997). Konica’s sales and research groups found that customers

only asked for minor improvements to the existing camera models. Kano, however,

believed that really new innovations did not come from simply listening to what

customers were verbally saying, but the development team had to develop a deep

understanding of customer’s real (latent) needs. Consequently, Konica staffers went to

commercial photo processing labs to investigate the actual prints taken by customers.

They found many mistakes and failures: blurry images, under and over exposure, blank

film rolls. Addressing these latent needs led to features such as auto focus, built-in-flash,

and automatic film rewinding that are widely available in cameras today.


9Other categories of needs have also been proposed. For example, Sanders (1992) identifies “observable needs” (that are displayed in action and can be determined through observation by experts), “explicit needs” (that can be expressed in words by customers), “tacit needs” (conscious needs that customers are unable to express in words), and “latent needs” (subconscious, possibly dormant, needs that customers are unable to express in words). Otto and Wood (2001) define “constant needs” (needs that are intrinsic to the task of the product; e.g., the number of exposures for a camera, whether implemented on film or the number if digital images that can be recorded), “variable needs” (needs that might disappear; e.g., digital photography eliminates the need for long film storage life), “general needs” (needs that apply to every customer in the population; e.g., the need for a camera to have a portable power source), and “niche needs” (needs that only apply to a relatively small segment of the population; e.g., underwater photography).

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The key concepts in Kano’s model are summarized in Exhibit 5. The horizontal

axis in this diagram indicates the degree to which a particular customer need is addressed

in a (new, existing) product or service, ranging from completely absent to completely

addressed. The vertical axis in this diagram indicates how satisfied the customer is for a

specific implementation of a customer need, ranging from delighted to disgusted. Within

this two-dimensional space, three different types of customer needs can be defined10.

The bottom curve, labeled basic needs, represents needs that are taken for granted

and typically assumed by the customer to be met (i.e., these are needs that “must be”

satisfied). “The camera works out of the box, the camera is safe, the battery can be

recharged by plugging into any outlet” are examples of basic needs for a digital camera.

These needs are the “order qualifiers” and thus must be of high quality; these needs are

needed to simply be in the game. Completely meeting basic needs cannot greatly

increase customer satisfaction, but if they are absent or below par customers will not

react favorably.

The middle curve, labeled performance needs, represent needs for which

customer satisfaction is roughly proportional to the performance exhibited by the product

or service (i.e., these needs are “linear” in that “more is better’). For example, longer

battery life in a digital camera and more internal memory for image storage are preferred.

These needs are frequently requested by customers during the course of traditional

market research studies, and are typically associated with predictable product

improvements (i.e., the “features” in Exhibit 2).

10Other types of needs can also be defined based on the reverse of the curves in Exhibit 5, as well as needs for which the customer is indifferent (along the horizontal axis). See Center for Quality of Management (1993) and Matzler and Hinterhuber (1998) for a detailed discussion of methods to collect customer information that can be used to classify needs into these types.

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The upper curve, labeled exciting needs, represent needs that the customer does

not expect to be satisfied. Thus, if this need is completely addressed the customer is

delighted but if not, the customer does not really care. These needs are the “order

winners” for customers. For example, side airbags, global positioning systems, air-less

tires that never get flat for automobiles might be exciting needs today (e.g., Mayersohn

2005).

The underlying message of the Kano model is simple, yet powerful. Customer

needs are dynamic in that an exciting need today will eventually migrate to being a

performance need and will become a basic need tomorrow (e.g., automobile air

conditioning was a delighter in the 1950’s but is a basic need today; more recently anti-

lock braking systems and cup holders that were once exciting needs have become

standard equipment in most automobiles). Thus, customer expectations increase over

time and, consequently, firms must continually strive to better understand evolving

customer needs in order to stay competitive.


Exhibit 6 summarizes the current theory and practice for understanding customer

needs. Interpreted needs (i.e., the voice of the customer must be “translated” into a needs

hierarchy) consist of articulated and unarticulated needs. Articulated needs are those

needs that a customer can readily verbalize, if asked appropriately. Unarticulated needs

are needs that customers cannot easily verbalize. It is important to keep in mind that

there are many reasons why customers say things (e.g., they believe it is what the

researchers want to hear; see Tourangeau, et al. 2000) and many reasons why they don’t

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say other things (including they didn’t remember, they didn’t want to tell, they didn’t

know how to tell, etc.).

Articulated needs generally involve information dealing with “what customers

say.” Traditional market research methods such as focus groups, personal depth

interviews, surveys, email questionnaires, and product clinics can be used to collect data

on articulated needs (e.g., Urban and Hauser 1993; McDonagh-Philp and Bruseberg

2000). Well-known market research methods include conjoint analysis, perceptual

mapping, segmentation, preference modeling, and simulated test markets (e.g., see the

reviews in Urban, et al. 1983; Green and Krieger 1989; Urban and Hauser 1993; Kaul

and Rao 1995; Urban 1996; Urban, et al. 1997; Green, et al. 2001). Information on

articulated needs can be obtained using category problem analysis (e.g., Tauber 1975;

Swaddling and Zobel 1996); see Exhibit 7 for an example. Other techniques include

repertory grids (Kelly 1955), Echo procedures (Barthol 1976), verbal protocols (Ericsson

and Simon 1984), laddering and means-ends analysis (Reynolds and Gutman 1988), as

well as projective techniques like product personality profiling, having customers draw

their ideal product, hypnosis, and archetype analysis (e.g., Shalit 1999).


Unarticulated needs generally involve information dealing with “what customers

do” and “what customers make” (see Sanders 1992). As suggested by Sanders and

Dandanate (1999), to deeply understand customer needs we need to learn about their

memories as well as their current and ideal experiences. To accomplish this, we can

listen to what customers say, we can interpret what customers express and make

inferences about what they think, we can watch what customers do, we can observe what

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customers use, we can uncover what customers know, we can reach toward

understanding what customers feel, and we can appreciate what customers dream.

Participant observation, applied (rapid) ethnography, and contextual inquiry are the

primary methods to find out what customers do. Common characteristics of these

methods are that they take place in the customer’s natural surroundings and that they are

open-ended in nature. For example, “listening” to what customers say can be

accomplished by taking notes of conversations and audio taping interviews; “observing”

what customers do is done by watching behaviors, making notes and mapping patterns of

behavior, sketching relationships between stakeholders, photographing or video taping

the general customer environment, using web cameras to watch activities; “observing”

what customers use can be performed by watching for unobtrusive behavior traces (e.g.,

wear and tear on artifacts and objects), watching or photographing or video taping

products and services being used, using web cameras (Sanders 2000). As example of

observing what customers do and use, see the series of photos in Exhibit 8. These photos

depict customers using barbeques at tailgating events before the big game. Key

unarticulated needs discovered by the development team included a need for the capacity

of a full-size grill, portability, comfort while cooking, safety, as well as quick cool down

and clean up. This ethnographic fieldwork, along with other market research, led to the

introduction of Char-Broil’s highly successful Grill2Go portable propane grill (see

Grill2Go 2004).


In addition to traditional ethnographic methods, it is possible to have customers

engage in self-reporting (e.g., studies involving diaries, beepers, daily logs, disposable

18

cameras, self-videotaping, web cameras; see Sanders 2002), have the development team

“be the customer” (e.g., collect currently available advertising and point-of-purchase

displays, analyze service and pricing options, visit retailers, talk to a salesperson, visit

company web sites, call customer support, etc.; see Griffin 1996; Otto and Wood 2001),

and/or conduct an artifact analysis of existing products and services. Human factors and

ergonomics research are other approaches to better understand what customers do (e.g.,

Salvendy 1997).

Participatory and collaborative design between the development team and

customer is the primary method for discovering what customers know, feel and dream

through what they make. Techniques include lead user analysis (e.g., von Hippel 1986;

von Hippel, et al. 1999), the use of customer toolkits (e.g., Thomke 2003; von Hippel

2001; Franke and Piller 2004; Urban and Hauser 2004), metaphor elicitation (Zaltman

1997; Christensen and Olson 2002), “serious play” using LEGOs (Roos, et al. 2004), as

well as making collages, cognitive image mapping, and Velcro modeling (Sanders 2000;

SonicRim 2004).

The discussion in this section indicates that a variety of traditional and

nontraditional market research approaches can be used to gain a rich understanding of

customer needs. Indeed, as recommended by Sanders (1992) multiple methods should be

used to have a complete coverage of the underlying needs. The information that can be

captured from these approaches differs quite a bit. In particular, the degree to which

customer needs must be interpreted from the original “raw” data increases as interest

moves from learning what customers say, to what customers do, to what customers make.

However, in all cases the customer “voice” must be translated into a hierarchy of needs.

19

A detailed discussion of techniques for translating data from these approaches into

interpreted needs is beyond the scope of this chapter. Excellent coverage of approaches

that have been successful in practice, including the use of the KJ analysis and affinity

diagrams to sort the huge amount of data generally collected into a needs hierarchy, are in

Burchill, et al. (1997), Burchill and Brodie (1997), Scupin 1997; Otto and Wood (2001),

Shillito (2001), Mello (2003), and Ulrich and Eppinger (2004), among others.

Future Research Directions

It is clear that innovation and new product development are challenging activities.

Innovations, especially those involving new technologies, are increasingly more complex

with many hundreds (if not thousands) of parts, involving dispersed development teams

of hundreds of people, and costing several million dollars in development before market

launch (e.g., Ulrich and Eppinger 2004). In addition, firms are under increasing pressure

to shorten their development times (e.g., Bayus 1997; Bayus, et al. 1997; Reinertsen

1997; Smith and Reinertsen 1998). And, the costs of studies to understand customer

needs are high11.


Under these conditions, it is not surprising that a lot of effort has been, and should

continue to be, on developing new methods for understanding customer needs. Naturally,

practicing design firms will continue to develop novel methods for understanding

customer needs (e.g., see Exhibit 9 for a selected summary of IDEO’s Method Cards).

11Urban and Hauser (2004) report the typical costs associated with different customer needs studies in the automobile industry. For example, qualitative/ethnographic interviews (5-10 groups of 5-10 customers each) covering 50-100 features or needs cost $40-50,000; tailored interviews for segmentation studies (800 personal interviews) including 73 scales cost $80,000; activities, interests, opinions studies (100,000 mailed questionnaires) covering 114 features or needs costs $500,000; conjoint analyses (300 on-line or in-person interviews) covering 10-20 features or needs costs $50-100,000; product clinics (300 central-facility personal interviews) covering 40-50 features or needs costs $500,000.

20

Academic research is also engaged in this activity. For example, Uran and Hauser (2004)

describe a relatively cost effective method for “listening in” as customers search the

Internet for information and advice about automobile purchases. Using a custom designed

web-based (virtual) advisor, customers can generate a large number of preferred

combinations of features, and, importantly, they can also reveal their needs for “new”

combinations not currently available. Dahan and Hauser (2002b) report several other

“virtual customer” methods: interactive web-based conjoint analysis, concept testing of

virtual prototypes, fast polyhedral adaptive conjoint estimation in which large numbers of

product features can be quickly screened and importance weights estimated, interactive

web-based environments where customers can design their ideal virtual prototypes, the

“information pump” that allows customers to interact in a web-based game with

incentives for customer to think hard and to verbalize the product features that are

important to them, stock-market-like securities trading where customers interact to

identify novel and winning concepts. Finch (1999) discusses how information from

customer product and service postings to Internet newsgroups gleaned from Usenet can

be used to understand customer needs. Fuller, et al. (2004) describe a method to harness

the innovative ideas within online communities, along with a virtual product development

lab, to generate information on customer needs. And, Nambisan (2002) proposes a

framework of how virtual customer communities can facilitate new product development.

Since information on needs must ultimately be obtained from customers, an

important direction for future research is to incorporate findings from the consumer

decision making literature dealing with “constructed preferences.” As reviewed by

Bettman, et al. (1998), a large body of research dealing with consumer decision making

21

argues that: (1) preferences among options critically depends on the customer’s goals, (2)

preferences depend on the complexity of the decision task, (3) preferences are highly

context dependent, (4) preferences depend on what is specifically asked of customers,

and (5) preferences depend on how the choice set is framed (e.g., losses loom larger than

gains; see Kahneman and Tversky 1979; Laibson and Zeckhauser 1998). The idea that

preferences are often constructed “on the fly” implies that the information available from

customers is highly sensitive to how the concept is communicated as well as context—

customers find it difficult to develop well-defined preferences and customers often bring

multiple goals to any decision problem (Bettman, et al. 1998). This line of research

provides a possible explanation for the inadequacy of traditional market research methods

in uncovering customer needs, as well as the success attributed to empathic, ethnographic

and the context specific approaches advocated by designers, sociologists, and

anthropologists. Other relevant research includes work on choice bracketing (Read, et al.

1999), construal processes (Fischoff, et al. 1999), choice deferral (Dhar 1997), contingent

valuation (e.g., Kahneman, et al. 1999), economic modeling and rationality (McFadden

1999), and measurement methods (Payne, et al. 1999). Relating work on the difficulty

customers have in making trade-offs seems particularly promising to enhance

understanding of customer needs. For example, research finds that consumers are

resistant to trading off some quality to get a better price and prefer paying a higher price

to get higher quality (e.g., Dhar and Simonson 1999; Nowlis and Simonson 1997; Luce,

et al. 1999). Other researchers argue that some product attributes are more difficult to

trade off than others (e.g., Tetlock 1992 calls these “sacred” values; Baron and Spranca

1997 discuss “protected” attributes). As also suggested by Bettman, et al. (1998),

22

continued research on the properties of customer needs (attributes) and the effects of

these properties on trade-offs is in order.

Finally, an especially interesting direction for future research is to develop a

comprehensive theory around what I call customer roadmapping. As discussed by

Sandia National Laboratories (2004), technology roadmapping is “a needs-driven

technology planning process to help identify, select, and develop technology alternatives

to satisfy a set of product needs.” Similarly, customer roadmapping is a customer

planning process to help identify and select key customer needs to be used as input into

the innovation and product development process. An important component of customer

roadmapping is a theory of “universal” customer needs dimensions that can be used as a

reference point for methods that collect needs information, as well as a starting point for

the construction of a hierarchy of specific needs for a particular context and segment of

customers. A set of universal needs dimensions would be an important input for planning

purposes since it would allow comparisons and benchmarking over time across products,

categories, and markets. If systematic patterns of evolution within these universal needs

dimensions can be established, customer roadmapping can be a useful forecasting tool12.

As an example, consider the following four “universal” customer needs dimensions that

might be associated with a product or service: (1) functionality (e.g., performance,

reliability, compatibility, flexibility), (2) form (e.g., aesthetics, durability, portability,

maintainability, uniqueness), (3) usability (e.g., ease of use, complexity), and (4) cost

(e.g., acquisition, use, disposal). Future research might establish the validity of these four

dimensions, and then develop a set of customer needs for the next level down. For

12For example, consider the work of Christensen (1997) and Christensen and Raynor (2003) on “disruptive innovations.” Although it does not seem to be based on rigorous research, they suggest a buying hierarchy in which customers want (in order): functionality, reliability, convenience, cost.

23

example, detailed “maps” of product functionality (McAdams, et al. 1999) and usability

(Jordan 1998; Han, et al. 2001; Babbar, et al. 2002) have been proposed, as have

universal “utility levers” for services (Kim and Mauborgne 2000) and scales for

uniqueness (Tian, et al. 2001). Reverse engineering of products can also be used to

construct the evolutionary path of product attributes (Otto and Wood 1998; McAdams, et

al. 1999).

Conclusion

Understanding customer needs is a crucial input into the innovation and new

product development process, and at the same time, it is a very challenging endeavor.

This chapter has attempted to review the literature relating to customer needs that spans

several disciplines. As the discussion in this chapter implies, much of the published

research related to customer needs has been concerned with the cross-fertilization of

ideas and concepts across disciplines (see Exhibit 10). Consequently, progress in fully

integrating a deep understanding of customer needs into the innovation process has been

slow. But, this review also indicates that the boundaries between the various functions

are coming down. There will always be a tradeoff between the expediency and cost

efficiency of practical methods for understanding customer needs versus methods of

obtaining a deeper understanding of needs that involve more effort and resources. There

also seems to be several directions that academic research can explore in the future. In

all cases though, the challenge will be to integrate across multiple disciplines. But, this is

what makes this topic interesting!


24

REFERENCES

Abras, C., D. Maloney-Krichmar, and J. Preece (2004), “User-Centered Design,” in W. Bainbridge (ed.), Berkshire Encyclopedia of Human-Computer Interaction, Great Barrington, MA: Berkshire Publishing Group.

Akao, Y. and G. Mazur (2003), “The Leading Edge in QFD: Past, Present and Future,” International Journal of Quality & Reliability Management, 20 (1), 20-35. Associated Press (2003), “Plans for Moist Toilet-Paper Rolls Unravel,” Miami Herald, September 2, www.miami.com/mld/miamiherald/business/6671201?1c.htm (accessed 12/12/03).

Aungst, S., R. Barton, and D. Wilson (2003), “The Virtual Integrated Design Method,” Quality Engineering, 15 (4), 565-579.

Austin, J. and J. Vancouver (1996), “Goal Constructs in Psychology: Structure, Process, and Content,” Psychological Bulletin, 120 (3), 338-375.

Babbar, S., R. Behara, and E. White (2002), “Mapping Product Usability,” International Journal of Operations & Production Management, 22 (9/10), 1071-1089.

Baron, J. and M. Spranca (1997), “Protected Values,” Organizational Behavior and Human Decision Processes, 70 (April), 1-16.

Barthol, R. (1976), “ECHO: Estimating Values in Familiar and Unfamiliar Cultures,” in H. Sinaiko and L. Broedling (eds.), Perspectives on Attitude Assessment: Surveys and Their Alternatives, Champaign, IL: Pendelton Press.

Bayus, B. (1997), “Speed-to-Market and New Product Performance Tradeoffs,” Journal of Product Innovation Management, 14 (Nov.), 485-497.

Bayus, B., S. Jain, and A. Rao (1997), “Too Little and Too Early: Introduction Timing and New Product Performance in the Personal Digital Assistant Industry,” Journal of Marketing Research, 34 (Feb.), 50-63.

Beebe, J. (1995), “Basic Concepts and Techniques of Rapid Assessment,” Human Organization, 54 (1), 42-51.

Bettman, J., M. Luce, and J. Payne (1998), “Constructive Consumer Choice Processes,” Journal of Consumer Research, 25 (3), 187-217.

Brand Strategy (2003), “Innovation: Where Have All the Ideas Gone?” Brand Strategy, (Nov.), 20.

25

http://www.miami.com/mld/miamiherald/business/6671201?1c.htm

Burchill, G., et al. (1997), Concept Engineering, Center for Quality of Management, Cambridge, MA, Document No. ML0080.

Burchill, G. and C. Brodie (1997), Voices into Choices: Acing on the Voice of the Customer, Madison, WI: Joiner/Oriel Inc.

Captain, S. (2004), “Making Sense of Specs,” New York Times, Dec. 23, www.nytimes.com/2004/12/23/technology/circuits/23spec.html?ex=1104642000&en=0631f3a84f5874fe&ei=5070&th (accessed 12/23/04).

Center for Quality of Management (1993), “Special Issue: Kano’s Method for Understanding Customer-Defined Quality,” Center for Quality of Management Journal, 2 (4), 3-36.

Chan, L., H. Kao, A. Ng, and M. Wu (1999), “Rating the Importance of Customer Needs in Quality Function Deployment by Fuzzy and Entropy Methods,” International Journal of Production Research, 37 (11), 2499-2518.

Christensen, C. (1997), The Innovator’s Dilemma, Boston: Harvard Business School Press.

Christensen, C. and M. Raynor (2003), The Innovator’s Solution, Boston: Harvard Business School Press.

Christensen, G. and J. Olson (2002), “Mapping Consumers’ Mental Models with ZMET,” Psychology & Marketing, 19 (6), 477-502.

Cooper, R. (1999), “From Experience: The Invisible Success Factors in Product Innovation,” Journal of Product Innovation Management, 16 (April), 115-133.

Crawford, M. and A. Di Benedetto (2003), New Products Management, New York: McGraw-Hill/Irwin.

Cyberkinetics, Inc. (2004), www.cyberkinetics.com (accessed 12/31/04).

Dahan, E. and J. Hauser (2002a), “Product Development: Managing a Dispersed Process,” in B. Weitz and R. Wensley (eds.), Handbook of Marketing, Thousand Oaks, CA: Sage Publications, 179-222.

Dahan, E. and J. Hauser (2002b), “The Virtual Customer,” Journal of Product Innovation Management, 19, 332-353.

Day, G., A. Shocker, and R. Srivastava (1979), “Customer-Oriented Approaches to Identifying Product-Markets,” Journal of Marketing, 43 (Fall), 8-19.

26

http://www.cyberkinetics.com/

http://www.nytimes.com/2004/12/23/technology/circuits/23spec.html?ex=1104642000&en=0631f3a84f5874fe&ei=5070&th

http://www.nytimes.com/2004/12/23/technology/circuits/23spec.html?ex=1104642000&en=0631f3a84f5874fe&ei=5070&th

Desmet, P., C. Overbeeke, and S. Tax (2001), “Designing Products with Added Emotional Value: Development and Application of an Approach for Research Through Design,” The Design Journal, 4 (1), 32-47.

Desmte, P. (2003), “A Multilayered Model of Product Emotions,” The Design Journal, 6 (2).

Dhar, R. (1997), “Context and Task Effects on Choice Deferral,” Marketing Letters, 8 (1), 119-130.

Dhar, R. and I. Simonson (1999), “Making Complementary Choices in Consumption Episodes: Highlighting Versus Balancing,” Journal of Marketing Research, 36 (Feb.), 49-44.

Dym, C., W. Wood, and M. Scott (2002), “Rank Ordering Engineering Designs: Pairwise Comparison Charts and Borda Counts,” Research in Engineering Design, 13, 236-242.

Eliashberg, J., G. Lilien, and V. Rao (1995), “Minimizing Technological Oversights: A Marketing Research Perspective,” in R. Garud, P. Nayyar, and Z. Shapira (eds.), Technological Innovation: Oversights and Foresights, New York: Cambridge University Press, 214-232.

Elliot, H. (1998), “Shoot First, Do Market Research Later,” Electronic Business, (Jan.), 49-50, 82.

Ericsson, K., & Simon, H. (1984), Protocol Analysis: Verbal Reports as Data, Cambridge, MA: MIT Press.

Farrell, C. (1993), “A Theory of Technological Progress,” Technological Forecasting and Social Change, 44, 161-178.

Finch, B. (1999), “Internet Discussions as a Source for Consumer Product Customer Involvement and Quality Information: An Exploratory Study,” Journal of Operations Management, 17, 535-556.

Fischoff, B. N. Welsh, and S. Frederick (1999), “Construal Processes in Preference Assessment,” Journal of Risk and Uncertainty, 19 (1-3), 139-164.

Franke, N. and F. Piller (2004), “Value Creation by Toolkits for User Innovation and Design: The Case of the Watch Market,” Journal of Product Innovation Management, 21 (6), 401-415.

Franklin, C. (2003), Why Innovation Fails, Rollinsford, NH: Spiro Press.

27

Fuller, J., M. Bartl, H. Ernst, and H. Muhlbacher (2004), “Community Based Innovation: A Method to Utilize the Innovative Potential of Online Communities,” Proceedings of the 37th Hawaii International Conference on System Sciences, (Jan.), 1-10.

Geistfeld, L., G. Sproles, and S. Badenhop (1977), “The Concept and Measurement of a Hierarchy of Product Characteristics,” in W. Perreault (ed.), Advances in Consumer Research, 4, Atlanta: Association for Consumer Research, 302-307.

Gershenson, J. and L. Stauffer (1999), “A Taxonomy for Design Requirements from Corporate Customers,” Research in Engineering Design, 11, 103-115.

Gershman, M. (1990), Getting It Right the Second Time, New York: Addison-Wesley.

Green, M., J. Linsey, C. Seepersad, K. Wood, and D. Jensen (2006), “Frontier Design: A Product Usage Context Method,” Proceedings of DETC/CIE, Philadelphia, PA.

Green, P. (1974), “A Multidimensional Model of Product-Features Association,” Journal of Business Research, 2 (2), 107-118.

Green, P. (1975), “Marketing Applications of MDS: Assessment and Outlook,” Journal of Marketing, 39 (Jan.), 24-31.

Green, P. and A. Krieger (1989), “Recent Contributions to Optimal Product Positioning and Buyer Segmentation,” European Journal of Operational Research, 41 (2), 127-141.

Green, P. and V. Srinivasan (1990), “Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice,” Journal of Marketing, 54 (Oct.), 3-19.

Green, P., A. Krieger, and Y. Wind (2001), “Thirty Years of Conjoint Analysis: Reflections and Prospects,” Interfaces, 31 (3), S56-S73.

Griffin, A. and J. Hauser (1992), “Patterns of Communication Between Marketing, Engineering, and Manufacturing – A Comparison Between Two New Product Teams,” Management Science, 38 (3), 360-373.

Griffin, A. and J. Hauser (1993), “The Voice of the Customer,” Marketing Science, 12 (1), 1-27.

Griffin, A. (1996), “Obtaining Customer Needs for Product Development,” in M. Rosenau, et al. (eds.), The PDMA Handbook of New Product Development, New York: John Wiley & Sons, 153-166.

Grill2Go (2004), www.grill2go.com (accessed 12/30/04).

28

http://www.grill2go.com/

Han, S., M. Yun, J. Kwahk, and S. Hong (2001), “Usability of Consumer Electronic Products,” International Journal of Industrial Ergonomics, 28, 143-151.

Hauser, J. (1984), “Customer Research to Focus R&D Projects,” Journal of Product Innovation Management, 2, 70-84.

Hauser, J. and D. Clausing (1988), “The House of Quality,” Harvard Business Review, 66 (May-June), 63-73.

Hauser, J. (1993), “How Puritan-Bennett Used the House of Quality,” Sloan Management Review, 34 (3), 61-70.

Henard, D. and D. Szymanski (2001), “Why Some New Products are More Successful than Others,” Journal of Marketing Research, 38 (3), 362-375.

Herzberg, F., B. Mausner, and B. Snyderman (1959), The Motivation to Work, New York: John Wiley.

Herzberg, F. (1968), “One More Time: How Do You Motivate Employees?” Harvard Business Review, 46 (1), 53-62.

Holtzblat, K. and H. Beyer (1993), “Making Customer-Centered Design Work for Teams,” Communications of the ACM, (Oct.), 93-103.

Huffman, C., S. Ratneshwar, and D. Mick (2000), “An Integrative Framework of Consumer Goals,” in S. Ratneshwar, et al. (eds.), The Why of Consumption, London: Routledge.

Iansiti, M. and E. Stein (1995), “Understanding User Needs,” Harvard Business School Note 9-695-051.

Johnson, M. and C. Fornell (1987), “The Nature and Methodological Implications of the Cognitive Representations of Products,” Journal of Consumer Research, 14, 214-228.

Jordan, P. (1998), An Introduction to Usability, Bristol, PA: Taylor & Francis.

Kahneman, D. and A. Tversky (1979), “Prospect Theory: An Analysis of Decision Making Under Risk,” Econometrica, 47 (March) 18-36.

Kahneman, D>, I. Ritov, and D. Schkade (1999), “Economic Preferences or Attitude Expressions? An Analysis of Dollar Responses to Public Issues,” Journal of Risk and Uncertainty, 19 (1-3), 203-235.

Kano, N., S. Tsuji, N. Seraku, and F. Takahashi (1984), “Attractive Quality and Must-Be Quality,” Hinshitsu: The Journal of Japanese Society for Quality Control, 14 (2), 39-48.

29

Karkkainen, H., K. Elfvengren, and M. Tuominen (2003), “A Tool for Systematic Assessment of Customer Needs in Industrial Markets,” International Journal of Technology Management, 25 (6/7), 588-604.

Kaul, A. and V. Rao (1995), “Research for Product Positioning and Design Decisions: An Integrative Review,” International Journal of Research in Marketing, 12, 293-320.

Kelley, T. (2001), The Art of Innovation, New York: Currency Books.

Kelly, G. (1955), The Psychology of Personal Constructs, New York: W.W. Norton.

Kim, W. and R. Mauborgne (2000), “Knowing a Winning Business Idea When You See One,” Harvard Business Review, 77 (Sept.-Oct.), 129-138.

Kirchner, P. (1995), Forgotten Fads and Fabulous Flops, Los Angeles: General Publishing Group.

Krishnan, V. and K. Ulrich (2001), “Product Development Decisions: A Review of the Literature,” Management Science, 47 (1), 1-21.

Kumar, V. and P. Whitney (2003), “Faster, Cheaper, Deeper User Research,” Design Management Journal, 14 (2), 50-57.

Laibson, D. and R. Zeckhauser (1998), “Amos Tversky and the Ascent of Behavioral Economics,” Journal of Risk and Uncertainty, 16, 7-47.

Lancaster, K. (1971), Consumer Demand: A New Approach, New York: Columbia University Press.

Leonard-Barton, D. (1995), Wellsprings of Knowledge, Boston: Harvard Business School Press.

Leonard, D. and J. Rayport (1997), “Spark Innovation Through Empathic Design,” Harvard Business Review, (Nov.-Dec.), 102-113.

Luce, M., J. Payne and J. Bettman (1999), “Emotional Trade-Off Difficulty and Choice,” Journal of Marketing Research, 36 (May), 43-159.

Martin, J. (1995), “Ignore Your Customer,” Fortune, 131 (8), 121-124.

Martin, M. (1999), Design for Variety: A Methodology for Developing Product Platform Architectures, Ph.D. dissertation in Mechanical Engineering, Stanford University, mml.stanford.edu/Research/Papers/1999/1999.DFV.DFM.martin/1999.DFV.DFM.martin.pdf (accessed 12/31/04).

Maslow, A. (1954), Motivation and Personality, New York: Harper and Row.

30

http://mml.stanford.edu/Research/Papers/1999/1999.DFV.DFM.martin/1999.DFV.DFM.martin.pdf

http://mml.stanford.edu/Research/Papers/1999/1999.DFV.DFM.martin/1999.DFV.DFM.martin.pdf

Masten, D. and T. Plowman (2003), “Digital Ethnography: The Next Wave in Understanding the Consumer Experience,” Design Management Journal, 14 (2), 75-83.

Matzler, K. and H. Hintehuber (1998), “How to Make Product Development Projects More Successful by Integrating Kano’s Model of Customer Satisfaction into Quality Function Deployment,” Technovation, 18 (1), 25-37.

Mayersohn, N. (2005), “Reinventing the Wheel (and the Tire, Too),” New York Times, Jan. 3, www.nytimes.com/2005/01/03/automobiles/03cars.html (accessed 1/3/05).

McAdams, D., R. Stone, and K. Wood (1999), “Functional Interdependence and Product Similarity Based on Customer Needs,” Research in Engineering Design, 11, 1-19.

McDonagh-Philp, D. and A. Bruseberg (2000), “Using Focus Groups to Support New Product Development,” Engineering Designer, 26 (5), 4-9.

McFadden, D. (1999), “Rationality for Economists?” Journal of Risk and Uncertainty, 19 (1-3), 73-105.

McMath, R. and T. Forbes (1998), What Were They Thinking? New York: Times Books.

Mello, S. (2003), Customer-Centric Product Definition, Boston: PDC Professional Pub.

Michalek, J., F. Feinberg, and P. Papalambros (2005), “Linking Marketing and Engineering Product Design Decisions via Analytical Target Cascading,” Journal of Product Innovation Management, 22 (1), 42-62.

Molotch, H. (2003), Where Stuff Comes From, New York: Taylor & Francis Books.

Montoya-Weiss, M. and R. Calantone (1994), “Determinants of New Product Performance: A Review and Meta-Analysis,” Journal of Product Innovation Management, 11 (5), 397-417.

Morita, A. (1986), Made in Japan, New York: Penguin Books.

Nagamachi, M. (1995), “Kansei Engineering: A New Ergonomic Consumer-Oriented Technology for Product Development,” International Journal of Industrial Ergonomics, 15, 3-11.

Nagamachi, M. (2002), “Kansei Engineering as a Powerful Consumer-Oriented Technology for Product Development,” Applied Ergonomics, 33, 289-294.

Nambisan, S. (2002), “Designing Virtual Customer Environments for New Product Development: Toward a Theory,” Academy of Management Review, 27 (3), 392-413.

31

http://www.nytimes.com/2005/01/03/automobiles/03cars.html

Nelson, E. (2002), “The Tissue that Tanked,” Wall Street Journal Classroom Edition, September, www.wsjclassroomedition.com/archive/02sep/MKTG.htm (accessed 12/12/03).

Norman, D. and S. Draper (eds.) (1986), User-Centered System Design: New Perspectives on Human-Computer Interaction, Hillsdale, NJ: Lawrence Earlbaum Associates.

Norman, D. (1988), The Psychology of Everyday Things, New York: Doubleday.

Nowlis, S. and I. Simonson (1997), “Attribute-Task Compatibility as a Determinant of Consumer Preference Reversals, Journal of Marketing Research, 34 (May), 205-218.

Olshavsky, R. and R. Spreng (1996), “An Exploratory Study of the Innovation Evaluation Process,” Journal of Product Innovation Management, 13, 512-529.

Otto, K. and S. Wood (1998), “Product Evolution: A Reverse Engineering and Redesign Methodolgy,” Research in Engineering Design, 10, 226-243.

Otto, K. and K. Wood (2001), Product Design, Upper Saddle River, NJ: Prentice Hall.

Papalambros, P. and D. Wilde (2000), Principles of Optimal Design: Modeling and Computation, New York: Cambridge University Press. Patnaik, D. and R. Becker (1999), “Needfinding: The Why and How of Uncovering People’s Needs,” Design Management Journal, 10 (2), 37-43.

Patton, A. (1999), “Deconstructing Design for Marketing: Tools for Accessing the Design Process,” Journal of Market Focused Management, 4, 309-319.

Payne, J., J. Bettman, D. Schkade (1999), “Measuring Constructed Preferences: Towards a Building Code,” Journal of Risk and Uncertainty, 19 (1-3), 243-270.

Pieters, R., H. Baumgartner, and D. Allen (1995), “A Means-End Chain Approach to Consumer-Goal Structures,” International Journal of Research in Marketing, 12, 227-244.

Power, C. (1992), “Will It Sell in Podunk? Hard to Say” Business Week, Aug. 10, 46-47.

Power, C. (1993), “Flops: Too Many Products Fail. Here’s Why – and How to Do Better,” Business Week, Aug. 16, 76-81.

Pullman, M., W. Moore, and D. Wardell (2002), “A Comparison of Quality Function Deployment and Conjoint Analysis in New Product Design,” Journal of Product Innovation Management, 19, 354-364.

32

http://www.wsjclassroomedition.com/archive/02sep/MKTG.htm

QFD Institute (2004), “Kansei Engineering Project: Mazda Miata,” www.qfdi.org/kansei_miata.htm (accessed 10/21/04).

Ratchford, B. (1975),”The New Economic Theory of Consumer Behavior: An Interpretive Essay,” Journal of Consumer Research, 2 (2), 65-75.

Ratneshwar, R. and A. Shocker (1991), “Substitution in Use and the Role of Usage Context in Product Category Structures,” Journal of Marketing Research, 28, 281-295.

Ratneshwar, S., A. Shocker, J. Cotte, and R. Srinivastava (1999), “Product, Person, and Purpose: Putting the Consumer Back into Theories of Dynamic Market Behavior,” Journal of Strategic Marketing, 7, 191-208.

Read, D., G. Loewenstein, M. Rabin (1999), “Choice Bracketing,” Journal of Risk and Uncertainty, 19 (1-3), 171-197.

Reinertsen, D. (1997), Managing the Design Factory, New York: Free Press.

Reynolds, T. and J. Gutman (1988), “Laddering Theory, Method, Analysis, and Interpretation,” Journal of Advertising Research, 28, 11-31.

Roos, J., B. Victor, and M. Statler (2004), “Playing Seriously With Strategy,” Long Range Planning, 37 (6), 549-568.

Rosen, S. (1974), “Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition,” Journal of Political Economy, 82 (Jan./Feb.), 34-55.

Saaty, T. (1988), The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, Pittsburgh: RWS Publications.

Salvendy, G. (1997), Handbook of Human Factors and Ergonomics, New York: Wiley-Interscience.

Sanders, E. (1992), “Converging Perspectives: Product Development Research for the 1990’s,” Design Management Journal, 3 (4).

Sanders, E. and U. Dandavate (1999), “Design for Experiencing: New Tools,” in C. Overbeeke and P. Hekkert (eds.), Proceedings of the First International Conference on Design and Emotion, Delft.

Sanders, E. (2000), “Generative Tools for CoDesigning,” in S. Scrivener, L. Ball, and A. Woodcock (eds.), Collaborative Design, London: Springer-Verlag, 3-12.

Sanders, E. (2002), “Ethnography in NPD Research: How ‘Applied Ethnography’ Can Improve Your NPD Research Process,” Visions, (April), www.pdma.org/visions/apr02/applied.html (accessed 1/3/05).

33

http://www.pdma.org/visions/apr02/applied.html

http://www.qfdi.org/kansei_miata.htm

Sandia National Laboratories (2004), “Fundamentals of Technology Roadmapping,” www.sandia.gov/Roadmap/home.htm (accessed 12/31/04).

Saranow, J. (2004), “The Puncture Wound I Got for Christmas,” Wall Street Journal, Dec. 30, D1,D3.

Schmitt, B. (1999), Experiential Marketing, New York: The Free Press.

Schnaars, S. 1989), Megamistakes: Forecasting and the Myth of Rapid Technological Change, New York: Free Press.

Scholtes, P. (1997), The Leader’s Handbook, New York: McGraw-Hill.

Schwartz, E. (2004), “The Sound War,” Technology Review, (May), 50-54.

Scupin, R. (1997), “The KJ Method: A Technique for Analyzing Data Derived from Japanese Ethnology,” Human Organization, 56 (2), 233-237.

Shalit, R. (1999), “The Return of the Hidden Persuaders,” Salon Media, www.salon.com/media/col/shal/1999/09/27/persuaders (accessed 1/03/05).

Shillito, M.L. (2001), Acquiring, Processing, and Deploying Voice of the Customer, New York: St. Lucie Press.

Shocker, A. and S. Srinivasan (1974), “A Consumer Based Methodology for the Introduction of New Product Ideas,” Management Science, 20 (6), 921-937.

Shocker, A. and S. Srinivasan (1979), “Multiattribute Approaches for Product Concept Evaluation and Generation: A Critical Review,” Journal of Marketing Research, 16 (May), 159-180.

Shocker, A., B. Bayus, and N. Kim (2004), “Product Complements and Substitutes in the Real World: The Relevance of ‘Other’ Products,” Journal of Marketing, 68 (Jan.), 28-40.

Smith, P. and D. Reinertsen (1998), Developing Products in Half the Time, New York: John Wiley & Sons.

SonicRim (2004), www.sonicrim.com (accessed 12/31/04).

Squires, S. (2002), “Doing the Work: Customer Research in the Product Development and Design Industry,” in Squires, S. and B. Byrne (eds.), Creating Breakthrough Ideas: The Collaboration of Anthropologists and Designers in the Product Development Industry, Westport, CT: Bergin and Garvey, 103-124.

34

http://www.sonicrim.com/

http://www.salon.com/media/col/shal/1999/09/27/persuaders

http://www.sandia.gov/Roadmap/home.htm

Squires, S. and B. Byrne (eds.) (2002), Creating Breakthrough Ideas: The Collaboration of Anthropologists and Designers in the Product Development Industry, Westport, CT: Bergin and Garvey.

Srinivasan, V. W. Lovejoy, and D. Beach (2001), “Integrated Product Design for Marketability and Manufacturing,” Journal of Marketing Research, 34 (Feb.) 154-163.

Stevens, G. and J. Burley (1997), “3,000 Raw Ideas = 1 Commercial Success!” Research-Technology Management, (May-June), 16-27.

Swaddling, J. and M. Zobel (1996), “Beating the Odds,” Marketing Management, 4 (4), 20-33.

Tauber, E. (1974), “How Market Research Discourages Major Innovation,” Business Horizons, 17 (June), 25.

Tauber, E. (1975), “Discovering New Product Opportunities with Problem Inventory Analysis,” Journal of Marketing, 39 (Jan.), 67-70.

Tetlock, P. (1992), “The Impact of Accountability on Judgement and Choice: Towards a Social Contingency Model,” in M. Zanna (ed.), Advances in Experimental Social Psychology, vol. 25, SanDiego: Academic Press, 331-376.

Thomke, S. (2003), Experimentation Matters: Unlocking the Potential of New Technologies for Innovation, Boston: Harvard University Press.

Tian, K., W. Bearden, and Hunter (2001), “Consumers’ Need for Uniqueness: Scale Development and Validation,” Journal of Consumer Research, 28 (June), 50-66.

Tourangeau, R., L. Rips, and K. Rasinski (2000), The Psychology of Survey Response, New York: Cambridge University Press.

Ulrich, K. and D. Ellison (1999), “Holistic Customer Requirements and the Design-Select Decision,” Management Science, 45 (5), 641-658.

Ulrich, K. and S. Eppinger (2004), Product Design and Development, New York: McGraw-Hill/Irwin.

Ulwick, A. (2005), What Customers Want, New York: McGraw Hill.

Urban, G., G. Katz, T. Hatch and A. Silk (1983), “The ASSESSOR Pre-Test Market Evaluation System.” Interfaces, 13 (6), 38-59.

Urban, G. (1996), “New Product Modeling: A 30 Year Retrospective and Future Challenges,” MIT Sloan Working Paper 3908-96, hdl.handle.net/1721.1/2625 (accessed 1/03/05).

35

http://hdl.handle.net/1721.1/2625

Urban, G. and J. Hauser (1993), Design and Marketing of New Products, Englewood Cliffs, NJ: Prentice Hall.

Urban, G. and J. Hauser (2004), “Listening In to Find and Explore New Combinations of Customer Needs,” Journal of Marketing, 68 (April), 72-87.

Urban, G., J. Hauser, W. Qualls, B. Weinberg, J. Bohlmann, and R. Chicos (1997), "Information Acceleration: Validation And Lessons From The Field," Journal of Marketing Research, 61 (1), 143-153.

von Hippel, E. (1986) "Lead Users: A Source of Novel Product Concepts," Management Science 32 (7), 791-805.

von Hippel, E. (2001), “Perspective: User Toolkits for Innovation,” Journal of Product Innovation Management, 18 (4), 247-257.

von Hippel, E., S. Thomke, and M. Sonnack (1999), "Creating Breakthroughs at 3M," Harvard Business Review, (Sept.-Oct.), 47-57.

Wasson, C. (2000), “Ethnography in the Field of Design,” Human Organization, 59 (4), 377-388.

Waters, S. and D. Field (2003), “The Segway Human Transporter: Developed with Passion and Principle,” Design Management Journal, 14 (2), 25-28.

Wilkie, W. and E. Pessemier (1973), “Issues in Marketing’s Use of Multi-Attribute Attitude Models,” Journal of Marketing Research, 10 (Nov.), 428-441.

Woodruff, R. and S. Gardial (1996), Know Your Customer: New Approaches to Understanding Customer Value and Satisfaction, Cambridge, MA: Blackwell Publishers.

Zaltman, G. (1997), “Rethinking Market Research: Putting People Back In,” Journal of Marketing Research, 23 (Nov.), 424-437.

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Exhibit 1The Innovation Space

Desirable Feasible

Salable

Highly Successful Innovations

Desirable Feasible

Salable

Highly Successful Innovations

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Exhibit 2An Example of Customer Needs for a Digital Camera

Desired End-States Consequences Features

Scene Mode

Auto flash

Auto red-eye correction

Optical & digital zoom lens

Palm-sized

Light WeightDesire

to relive fond

memories

Is convenientto use

It’s easyto use

Feel confident

taking photos

Takesgreat

photos

Is portable

Can easilyshare photos Can tag photos

Easy to transfer photos

Easy to review photos

Quick start-up

Long lasting battery

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Exhibit 3The Languages of New Product Development

Customer Needs(and Wants)

Customer Requirements

Product Specs

Product Characteristics

Product Attributes

Customer Needs(and Wants)

Customer Requirements

Product Specs

Product Characteristics

Product Attributes

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Exhibit 4The Fuzzy Front-End of New Product Development

ConceptGeneration, Screening,Testing & Selection

Establish Target Requirements & Specs

IdentifyCustomer Needs

Develop PrioritizedNeeds Hierarchy








Voice of the Customer












Voice of the Customer

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Exhibit 5The Kano Model of Customer Satisfaction

CustomerDelighted

CustomerDisgusted

Need CompletelyAddressed

Need Completely

Ignored

Exciting Needs

Performance Needs

Basic Needs

CustomerDelighted

CustomerDisgusted

Need CompletelyAddressed

Need Completely

Ignored

Exciting Needs

Performance Needs

Basic Needs

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Exhibit 6Approaches for Understanding Customer Needs

Interpreted Needs• Basic Needs• Performance Needs• Exciting Needs

Unarticulated Needs

What Customers Say

What Customers Do

What Customers Make

Market Research

Participant Observation Applied EthnographyHuman Factors & Ergonomics Research

Collaborative Design

Articulated Needs

Interpreted Needs• Basic Needs• Performance Needs• Exciting Needs

Unarticulated Needs

What Customers Say

What Customers Do

What Customers Make

Market Research

Participant Observation Applied EthnographyHuman Factors & Ergonomics Research

Collaborative Design

Articulated Needs

Articulated Needs

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Exhibit 7Example of Category Problem Analysis for Sandwich Bags

Consumer Attitudes and Behaviors

How often do you need to wrap food such as sandwiches? What kind of food do you need to

wrap? How long does it usually take? How do you currently wrap food? How do you know

when the food is wrapped? How do you feel when you need to wrap sandwiches? What

frustrates you when you wrap food?

Benefits Sought

What are the things (tangible and intangible) you want in sandwich wrap? How are

important are these benefits to you?

Problems Consumers Encounter

What types of food are most difficult to wrap? What things do you dislike the most with

your current way of wrapping food? What would you change with your current

“product?”

Solutions and Methods Used

How do you handle the problems you mentioned? What products do you believe are the

“gold standard” for wrapping food? What do these products do that the others do not?

Why don’t you use these products?

Aspects of Ideal Solution

What would you like an “ideal” solution to do for you?

What are the relevant met and unmet needs and problem areas for the customer?

• What is the essence of the consumer need?• Why does the need exist?• Which benefits and attributes are mandatory? • Which benefits are consumers willing to “trade-off?”• What benefits are available to the consumer? • What benefits does the consumer most desire?• What factors might drive purchase decisions in the category?

What are the relevant met and unmet needs and problem areas for the customer?

• What is the essence of the consumer need?• Why does the need exist?• Which benefits and attributes are mandatory? • Which benefits are consumers willing to “trade-off?”• What benefits are available to the consumer? • What benefits does the consumer most desire?• What factors might drive purchase decisions in the category?

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Exhibit 8Example of Ethnographic Fieldwork at Tailgating Events

(source: Char-Broil)

“I like my pig well done!” (Customers use full-sized grills, transporting them to and from the game.)

Portable grilling can be very uncomfortable!

Current grilling methods can be unsafe (people drinking before the game, vehicles, fire hazard).

“I gotta get to the game! I hope nobody steals my grill.”

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Exhibit 9Selected Method Cards from IDEO

1. Extreme User InterviewsIdentify individuals who are extremely familiar or completely unfamiliar with the product and ask them to evaluate their experience using it.

2. Rapid EthnographySpend as much time as you can with people relevant to the design topic. Establish their trust in order to visit and/or participate in their natural habitat and witness specific activities.

3. Behavioral ArchaeologyLook for the evidence of people’s activities inherent in the placement, wear patterns, and organization of places and things.

4. Social Network MappingNotice different kinds of social relationships within a user group and map the network of their interactions.

5. Error AnalysisList all the things that can go wrong when using a product and determine the various possible causes.

6. Predict Next Year’s HeadlinesInvite clients to project their company into the future, identifying how they want to develop and sustain customer relationships.

7. Camera JournalAsk potential users to keep a written and visual diary of their impressions, circumstances, and activities related to the product.

8. Cognitive MapsAsk Participants to map an existing or virtual space and show how they navigate it.

9. Empathy ToolsUse tools like clouded glasses and weighted gloves to experience processes as though you yourself have the abilities of different users.

10. Activity AnalysisList or represent in detail all tasks, actions, objects, performers, and interactions involved in a process.

11. Cognitive Task AnalysisList and summarize all of a user’s sensory inputs, decision points, and actions.

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12. Unfocus GroupAssemble a diverse group of individuals in a workshop to use a stimulating range of materials and create things that are relevant to your project.

13. Draw the ExperienceAsk participants to visualize an experience through drawings and diagrams.

14. A Day in the LifeCatalog the activities and contexts that users experience throughout an entire day.

15. Cultural ProbesAssemble a camera journal kit (camera, film, notebook, instructions) and distribute it to participants within one or across many cultures.

16. ScenariosIllustrate a character-rich story line describing the context of use for a product or service.

17. Experience PrototypeQuickly prototype a concept using available materials and use it in order to learn from a simulation of the experience using the product.

18. BodystormingSet up a scenario and act out roles, with or without props, focusing on the intuitive responses prompted by the physical enactment.

19. Try it yourselfUse the product or prototype you are designing.

20. Behavioral MappingTrack the positions and movements of people within a space over time.

21. Role-PlayingIdentify the stakeholders involved in the design problem and assign those roles to members of the team.

22. Behavior SamplingGive people a pager or phone and ask them to record and evaluate the situation they are in when it rings.

23. Card SortOn separate cards, name possible features, functions, or design attributes. Ask people to organize the cards spatially, in ways that make sense to them.

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24. ShadowingTag along with people to observe and understand their day-to-day routines, interactions, and contexts.

25. Historical AnalysisCompare features of an industry, organization, group, market segment, or practice through various stages of development.

26. Still-Photo SurveyFollow a planned shooting script and capture pictures of specific objects, activities, etc.

27. NarrationAs they perform a process or execute a specific task, ask participants to describe aloud what they are thinking.

28. Personal InventoryDocument the things that people identify as important to them as a way of cataloging evidence of their lifestyles

29. Character ProfilesBased on observations of real people, develop character profiles to represent archetypes and the details of their behavior or lifestyles.

30. Be Your CustomerAsk the client to describe, outline, or enact their typical customer’s experience.

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Exhibit 10The Cross-Fertilization of Research on Customer Needs

Engineering/Operations/Quality• customer requirements, product specs• QFD•VOC

Design/Sociologys/Anthropology• needs, wants, desires• empathic design• applied ethnography

Marketing/Economics/Psychology• product characteristics, attributes• conjoint analysis• perceptual mapping, preference modeling

Desirable Feasible

Salable

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understanding customer needs

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